In order to address the issue of increasing bandwidth requirements demanded for wireless communication systems, different schemes are being developed to allow multiple user terminals to communicate with a single access point by sharing the same channel (same time and frequency resources) while achieving high data throughputs. Spatial Division Multiple Access (SDMA) represents one such approach that has recently emerged as a popular technique for the next generation communication systems. SDMA techniques may be adopted in several emerging wireless communications standards such as IEEE 802.11 (IEEE is the acronym for the Institute of Electrical and Electronic Engineers, 3 Park Avenue, 17th floor, New York, N.Y.) and Long Term Evolution (LTE).
In SDMA systems, an access point may transmit or receive different signals to or from a plurality of user terminals at the same time and using the same frequency. In order to achieve reliable data communication, signals dedicated to different user terminals may need to be mutually orthogonal and located in sufficiently different directions. Independent signals may be simultaneously transmitted from each of multiple space-separated antennas at the access point. Consequently, the combined transmissions may be mutually orthogonal and/or directional; i.e., the signal that is dedicated for each user terminal may be relatively strong in the direction of that particular user terminal, and sufficiently weak in directions of other user terminals. Similarly, the access point may simultaneously receive on the same frequency the combined signals from multiple user terminals through each of multiple antennas separated in space, and the combined received signals from the multiple antennas may be split into independent signals transmitted from each user terminal by applying the appropriate signal processing technique.
A multi-antenna communication system employs multiple transmit antennas at a transmitting entity and one or more receive antennas at a receiving entity for data transmission. The multi-antenna communication system may thus be a multiple-input multiple-output (MIMO) system. The MIMO system employs multiple (Nt) transmit antennas and multiple (Nr) receive antennas for data transmission. A MIMO channel formed by the Nt transmit antennas and the Nr receive antennas may be decomposed into Nsh spatial channels, where Nsh≦min{Nt,Nr}. The Nsh spatial channels may be used to transmit Nsh independent data streams in a manner to achieve greater overall throughput.
In a multiple-access MIMO system based on SDMA, an access point can communicate with one or more user terminals at any given moment. If the access point communicates with a single user terminal, then the Nt transmit antennas are associated with one transmitting entity (either the access point or the user terminal), and the Nr receive antennas are associated with one receiving entity (either the user terminal or the access point). The access point can also simultaneously communicate with multiple user terminals via SDMA. In general, for SDMA, the access point utilizes multiple antennas for data transmission and reception, and each of the user terminals typically utilizes less than the number of access point antennas for data transmission and reception.
Good performance (e.g., high transmission capacity and low error rate) can be achieved by transmitting data on eigenmodes of MIMO channels between the access point and every individual user terminal. The eigenmodes may be viewed as orthogonal spatial channels. The transmission on eigenmodes may provide decreased inter-user interference, as well as decreased interference between different spatial streams simultaneously transmitted from the access point antennas and dedicated to a single user terminal. Every user terminal may estimate a MIMO channel response, perform singular-value decomposition of the channel matrix, select one or more most reliable eigenmodes (i.e., eigenmodes with the largest eigenvalues), and send to the access point via feedback the corresponding quantized eigenvectors along with related eigenvalues and channel quality information (CQI). The access point may then generate the precoding matrix and perform spatial processing (beamforming) using the generated precoding matrix in order to multiplex data to different user terminals with reduced inter-user interference.
In the prior art, the precoding matrix is generated at the access point based on a multiuser eigenmode transmission (MET) (e.g., as specified in Boccardi, F. and Huang, H., A Near-optimum technique using linear precoding for the MIMO broadcast channel, IEEE International Conference on Acoustics, Speech and Signal Processing, April 2007). In this particular approach, a subset of eigenmodes can be selected at every user terminal and a linear spatial preprocessing (beamforming) can be applied at the access point on selected eigenmodes using a block-diagonalization technique that ensures orthogonality between distinct user terminals. The precoding at the access point can be also based on the zero-forcing (ZF) technique and extended for a system with multiple antennas at user terminals: the ZF2 technique. The ZF2 technique also ensures that there is no inter-user interference between distinct user terminals.
The performance of precoding techniques from the prior art can be evaluated in terms of a transmission capacity that represents a number of data bits per transmission dedicated to all user terminals in the system. Compared to the theoretical bound, a certain performance gap can be observed due to the interference between different spatial streams that are dedicated to the same user terminal.
Therefore, there is a need in the art for an improved precoding method to increase the transmission capacity in the multiuser wireless system.